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A Complete-Electrode-Model-Based Forward Approach for Transcranial Temporal Interference Stimulation with Linearization: A Numerical Simulation Study

Numerical Analysis 2026-02-05 v2 Numerical Analysis

Abstract

Background and Objective: Transcranial temporal interference stimulation (tTIS) is a promising non-invasive brain stimulation technique in which interference between electrical current fields extends the possibilities of electrical brain stimulation. The objective of this study is to develop an efficient mathematical tTIS forward modelling scheme that allows for realistic and adaptable simulation and can be updated accurately when the contact resistance is modified in one or more electrodes. Such a model is vital, for example, in optimization processes that seek the best possible stimulation currents to exhibit or inhibit a given brain region. This study aims to establish and evaluate the complete electrode model (CEM), i.e., a set of boundary conditions incorporating electrode impedance and contact patch, as a forward finite-element-method-based simulation technique for tTIS and investigate linearized CEM as a surrogate. Results: The CEM-based forward simulation successfully reproduced the volumetric stimulating fields induced by tTIS. Sensitivity analysis showed that variations in electrode resistance affects the field distribution, especially in regions where the interfering currents have nearly equal amplitudes. The linearized CEM model closely matched the full nonlinear model within a predefined peak signal-to-noise ratio (PSNR) threshold for relative error. Both models exhibited the highest sensitivity near the focal region.

Keywords

Cite

@article{arxiv.2506.18436,
  title  = {A Complete-Electrode-Model-Based Forward Approach for Transcranial Temporal Interference Stimulation with Linearization: A Numerical Simulation Study},
  author = {Santtu Söderholm and Maryam Samavaki and Sampsa Pursiainen},
  journal= {arXiv preprint arXiv:2506.18436},
  year   = {2026}
}

Comments

19 pages; 23 figures; Submitted to Biomedical Signal Processing and Control

R2 v1 2026-07-01T03:29:05.157Z